Iran. J. Chem. Chem. Eng. Research Article Vol. 39, No. 5, 2020

Research Article 239

A Hybrid Membrane-Absorption Process

for Carbon Dioxide Capture:

Effect of Different Alkanolamine on Energy Consumption

Nasir, Qazi*+

Department of Chemical and Petrochemical Engineering, College of Engineering and Architecture,

University of Nizwa, OMAN

Suleman, Humbul

Department of Chemical and Biochemical Engineering, AT-CERE, Technical University of Denmark,

DENMARK

Elumalai, Manivannan

International Maritime College, OMAN

ABSTRACT: Amine and membrane-based processes are commonly used to treat acid gases such as

carbon dioxide and hydrogen sulfide. Carbon dioxide adversely affects the environment, therefore,

its utilization and storage are critical. In this work, a simplistic approach of single-stage membrane

units combine with amine absorption processes with different commercial amines was investigated.

An increase in CO2 concentration in the feed gas results in a substantial increase in the thermal energy

consumption of the stripper reboiler were using a hybrid amine-membrane setup can effectively reduce

energy consumed in the reboiler. Both the amine absorption process and membrane process

are simulated using Aspen HYSYS V10. Since the membrane is not available in Aspen HYSYS V10

unit operation package; it is programmed and added as custom user operation. Moreover, a new acid/

amine-based fluid package builds in a combination of the Peng-Robinson equation of state for vapor

phase and electrolyte non-random two liquid-based activity model for the liquid phase were used

in this study. Furthermore, energy consumption in CO2 capture using different alkanolamine such as

N-methyldiethanolamine (MDEA), monethanolamine (MEA), deithanolamine (DEA), piperazine (PZ),

triethanolamine (TEA) are also studied. As membrane unit help in CO2 reduction in feed to amine

absorption process in hybrid amine-membrane setup. This significantly reduces the energy

requirement as compared to the conventional standalone alkanolamine process. In comparison

with various amines used in the amine absorption process, MEA offers the lowest total energy

consumed, whereas, MDEA is considered to be the highest in terms of energy consumption.

KEYWORDS: Amine absorption process; Membrane process; Hybrid process; Aspen HYSYS;

MEA; DEA.

* To whom correspondence should be addressed.

+ E-mail: qazinasir@unizwa.edu.om ; qazinasir@gmail.com

1021-9986/2020/5/239-254 17/$/6.07

Iran. J. Chem. Chem. Eng. Nasir Q. et al. Vol. 39, No. 5, 2020

240 Research Article

INTRODUCTION

Natural gas that is brought to the well head from

underground is much different from the gas which

is consumed as a fuel in various applications worldwide.

Natural gas composition is not consistent and varies

with different geographical location of the World. Methane

is a primary component of natural gas accounting 75 – 90 %,

whereas, ethane, propane, butane accounts for 1 – 3 % and

the rest consists of higher hydrocarbons [1]. Natural gas

deposits may also contain complex contaminants such as

carbon dioxide (CO2), hydrogen sulphide (H2S), mercury,

water and Benzene, Toluene and Xylene (BTX), which

contributes to the environmental hazards. In recent years,

the removal of CO2 from natural gas has captured interest

due to high demand of pipeline-grade gas specification.

The presence of CO2 in the well in combination with water

tends to cause corrosion to pipelines and process

equipment. Moreover, the existence of CO2 in the NG

not only reduces the heating value of gas but also cause

crystallization during liquefaction process [2, 3].

Across the globe, considerable variation of CO2

content in natural gas has been encountered, where CO2

percentage in raw natural gas varies from 4 to 50 % and

some cases even as high as 98% [4]. Efficient process

scheme is required to remove CO2 from NG. Presently,

processes such as absorption (chemical and physical),

adsorption (solid surface), hybrid (physical and chemical),

membrane and cryogenic separation are used to remove

CO2 from natural gas [5]. To capture CO2 from flue gas,

alkanolamine-based absorption processes are considered

as a well-commercialized technology due to their large

handling capacity, and capability to operate at low CO2

concentrations and low pressure of exhaust/flue gases.

However, increase in CO2 concentration, the process

becomes energy intensive [6]. The post-combustion

treatment of the flue gas in a fossil fuel power plant

is commonly employed using a chemical solvent based

approach where usually an alkanolamine solution is used

for CO2 absorption [7]. In this approach, the feed flue gas

with CO2 concentration of 12-15 mol% is in contact

with 30 % aqueous monoethanolamine (MEA) solution

in the absorption column. Then the CO2-rich aqueous MEA

solution is sent to the stripping column for the regeneration

using steam temperature of 120 oC and CO2 is

subsequently recovered after condensation of the water

vapors [8]. This solvent regeneration in the stripper is

an energy intensive step in a conventional alkanolamine

based absorption process. This happens due to the reboiler

heat duty where extensive amount of heat is required

for stripping the gas from the liquid solvent by using steam,

the heat of reaction for CO2 desorption and lastly,

the sensible heat that is used to raise the temperature of

the rich solvent [8]. A Gas Pessurized Stripping (GPS) is

an adaptive alternative route which uses high pressure

and non-condensable stripping gas to strip the CO2 off the CO2

laden solvent stream [9]. The advantage of GPS column

of being less energy intensive which significantly reduced

heat loss due to stripping heat. But the additional

separation requirement for CO2 and the stripping gas is

a mere drawback.

Alternatively, membrane based CO2 separation is

a maturing and commercially proven technology for natural

gas processing [1, 10-12]. In contrast to the traditional amine

process, membrane processes are relatively simpler and

have low energy cost due to no phase change during

the separation [13]. Polymeric or inorganic membrane

consisting of zeolite, sol-gel silica or carbon molecular sieve

is used for CO2 separation by difference in diffusion rates

and adsorption strength of resulting component mixture

in polymer matrix or in organic membrane pores. In membrane

process, the gas permeation involves dissolution in high

pressure side of the membrane, diffusion across the

membrane wall and subsequently, evaporation from

the low-pressure side. As a result, some gases are more soluble

and permeate through polymeric membrane and other gases

retentate [14-16]. However, the post-combustion treatment

of flue gases (e.g. in coal fired power plants) using

membrane separation processes are challenging due

to the low CO2 partial pressure of flue gas and requires

a significant partial pressure drive for effective separation [10, 17].

Therefore, compression on the feed side (membrane

upstream) and vacuum on permeate (downstream) side

is subsequently required. However, considering the sheer

volume of flue gas, compression and vacuum process results

in a substantial increase in equipment and energy costs

which ultimately, increase Cost of Equipment (COE) over

amine absorption process [10, 18]. Furthermore, power

plants require large surface area of membrane which could

expand up to millions of square meters of membrane area.

Such large surface area of high performance membrane is

difficult to manufacture and handle and it is operationally

enviable at such a scale.

Iran. J. Chem. Chem. Eng. A Hybrid Membrane-Absorption Process for Carbon Dioxide Capture: ... Vol. 39, No. 5, 2020

Research Article 241

The membrane and GPS technology could be possibly

an attractive option to treat gas mixture with high CO2

content. Moreover, most of contaminates are already

removed in pretreatment stage, which enhances

the separation of acid gases in the amine unit and also enhance

life of membrane. Therefore, to benefit from technologies,

CO2 capture in combination with membrane and amine,

also known as hybrid CO2 capture process could be used

as an attractive option on a large scale separation

processes.

In this work, a hybrid scheme of membrane

technology, and amine absorption unit, is conjoined

to achieve acid gas removal economically. Alkanolamine

based absorption process is simulated in Aspen

HYSYS environment and since membrane unit is not

a predefined unit in Aspen HYSYS, complete mixing

model for membrane is coded in the custom user

operation module of Aspen HYSYS. The model

is then used for the prediction of CO2 separation using

membrane process and connected with Aspen HYSYS,

respectively [19].

THEORITICAL SECTION

Membrane process

Different arrangement/ configuration of permeator

are commonly employed for the design of the membrane

separation processes along with the specification of

process unit such as size and its operating conditions.

Therefore, the most common and simplest design

arrangements are the single stage or double stage with

either permeate or retentate with or without recycle stream.

The recovery of the desired component can be enhanced

using recycle or multistage with recycle configuration

[20]. However, in this study to avoid calculation

complexities which could arise later in hybrid process

scheme, a simple single stage arrangement without recycle

is used for the membrane unit. The complete mixing model

on permeate and high-pressure side is assumed for

the membrane permeation. Therefore, any point along

the membrane is determined by relative rates of the feed

composition. The model is based on the mass balance over

a differential element of hollow fiber membrane. Since,

the model is not available in a standard version of Aspen

HYSYS, it was implemented/ coded in Aspen HYSYS

program, using custom user unit operation with the help of

visual basic language [19].

Table 1: Feed conditions for membrane process[21].

Membrane Hollow fiber

Flow configuration Cross-flow (complete mixing)

Components permeance

cm3 STP

s. cm2. cm of hg)

CH4 = 8.50e-11

CO2 = 3.50e-11

C2H5 = 5.80e-9

H2S = 4.0e-9

Temperature (oC) 37.8

Feed pressure / retentate (bar) 36.2

Permeate pressure (bar) 1.013

Membrane replacement is usually cost intensive,

therefore pretreatment of feed gas is commonly required

to extend the life of the membrane. In this study, the feed gas

was considered pretreated, and assumed that the minor

components such as SOx, NOx, CO, H2O and ash are not

present. Such components especially moisture content

in the feed gas decrease the life of the membrane therefore,

pretreatment are necessary. In the calculation, the gas used

in this work was assumed free from moisture and

considered to contain overall high composition of CH4 and

CO2, which is most common in CO2 rich natural gas

reservoirs. The conditions such as flow rate, composition,

temperature and pressure for the feed gas used in the

Gas Permeation Unit (GPU) is presented in Table 1. The CH4

content in the feed gas ranges from 30 to 70 %, whereas

the concentration of CO2 varies from 10 to 50%.

The product target varies, and the goal is to reduce the CO2

content in the feed gas by the membrane process, before

being treated in the amine process.

Membrane model used

Complete-mixing model used in this study for gas

separation by membrane is shown in Fig. 1. There

is a minimal change in the composition if the separation

element is operated at a low recovery which means the

permeate flow rate is a small fraction of the entering feed

rate. Complete mixing model provides a reasonable

estimate of permeate purity. As shown in Fig. 1, qf, q0 and

qp is feed, retentate and permeate total flow rates, is

fraction feed permeated. Detailed description of the

derivation of the model equations is stated elsewhere [22].

Since, the hybrid setup consists of membrane and

amine absorption processes, it involves a complex set

Iran. J. Chem. Chem. Eng. Nasir Q. et al. Vol. 39, No. 5, 2020

242 Research Article

Fig. 1: Schematic of complete mixing model.

Fig. 2: Single stage (SS) membrane configuration used.

of mathematical equations which increases the

computation complexity, especially the amine absorption

process due to its highly nonlinear nature, together with

large recycle stream. The multi-stage permeator design

pose more computational difficulties due to the complex

set of differential and algebraic equations. Therefore,

a simplistic approach consisting of a single stage membrane

configuration is used in this work. A membrane process

setup used is shown in Fig. 2, whose primary focus

is the moderate purity and recovery requirement from single

stage [20].

Amine base absorption process

The retentate composition from the membrane unit

is further treated in the alkanolamine absorption process with

amine regeneration configuration, also simulated in Aspen

HYSYS V10. The composition of both CH4 and CO2

captured from both membrane and amine unit was

compared. In amine process different solvents (in

standalone or combination are used) and compared, i.e.,

monoethanolamine (MEA), N-methyldiethanolamine (MDEA),

diethanolamine (DEA), combination of MDEA + DEA,

MDEA + DEA + MEA, MDEA + MEA and MDEA+

Piperazine are studied for the treatment of acid gas,

which prime focus is to vary CO2 and CH4 content

while keeping H2S content constant. The comparison of

different solvent-based separation techniques and their

effects on the reduction of the thermal energy consumption

are also found elsewhere [23, 24]. For illustration purpose,

the conventional MDEA process flowsheet for the removal

of acid gas are shown in Fig. 3. To elaborate further, CO2

rich natural gas enters the absorber where they are

in contact with aqueous solution of MDEA flowing counter-

current to the gas stream. An exothermic reaction between

a weak base (MDEA) and a weak acid (CO2) takes place

to form water soluble salts. The CO2 rich MDEA stream

exits the absorber at the bottom of the absorber, whereas,

the sweet gas from the top. The bottom stream pressure

is then reduced and to be further sent to separator where

light hydrocarbons (HC) are separated from rest of

the components. The components are then preheated in a heat

exchanger by lean MDEA stream leaving the bottom of

the stripper. The MDEA containing CO2 stripped off leaves

the top of the stripper column, whereas, the lean MDEA

is recycled back to the absorber. As amine process

encompass a substantial amount of energy for regeneration

of the used solvent at the stripper reboiler, the thermal

energy required at the stripper was considered as a main

energy penalty in the amine process.

In order to simulate amine absorption process in Aspen

HYSYS, several electrolyte-based physical property methods

(EoS) are available for processes containing CO2, H2O

and MDEA. These property methods utilize the electrolyte-NRTL

(activity-based approach) to calculate the transport and

thermodynamic properties in the liquid phase.

However, in this work, a new property method that

is recently incorporated in Aspen HYSYS V10, for acid gas

and chemical solvents based absorption systems is used.

This property package is selected prior to entering

the setup in the flowsheet environment. Acid Gas-Chemical

solvent property package are updated and enhanced

in version V10 of Aspen HYSYS. The property package

is based on extensive research and development in areas

such as rate-based, chemical absorption process and molecular

thermodynamic models for aqueous amine solution [25].

The property package utilizes Peng-Robinson

equation-of-state for vapor phase prediction and the

Iran. J. Chem. Chem. Eng. A Hybrid Membrane-Absorption Process for Carbon Dioxide Capture: ... Vol. 39, No. 5, 2020

Research Article 243

Fig. 3: Acid gas cleaning using MDEA.

electrolyte Non-Random Two-Liquid (e-NRTL) activity

coefficient model for liquid phase prediction, respectively [26].

The e-NRTL model improved due to the thermodynamic

and transport property model parameters which are identified

by regression of extensive thermodynamics and physical

property literature data for aqueous alkanolamine

solutions. The e-NRTL model predictability is improved

using the available VLE and heat absorption data which

is used to perform the regression analysis for all supported

alkanolamine solvents, commonly used in the industry

[27]. Detailed information regarding the Acid Gas

property package is available in Aspen HYSYS V10 help

section [19]. One of the initial requirement to setup the

simulation using Acid Gas property package, is that at least

one amine component must be added in the component list

along with CO2, H2O and H2S which otherwise prompted

with error.

Hybrid (amine/membrane) based approach

Amine separation technology is conventional way

for the removal of acid gas from natural gas stream.

Alternatively, membrane process is used for the removal

of acid gases and is most commonly used prior to amine

absorption process. Combination of membrane and amine

process also referred as hybrid process, as shown in Fig. 4,

can be used and utilizes the benefit of both the

technologies. In this study, a simplistic approach for

sweetening process is used. It consists of a single-stage

membrane permeator combined with amine absorption

process. Various solvents and their combination are used.

The natural gas stream containing high concentration of

acid gas is first treated by the membrane process to remove

most of the acid gas before additional purification

by alkanolamine absorption process. The hybrid process

setup and their specified parameters used for the hybrid

process are shown in Fig. 4.

RESULTS AND DISCUSSION

Membrane Model validation

The complete mixing mathematical model used

in this study for the membrane process were validated using

the experimental data reported by Tranchino et al. [28].

The data were collected using a composite hollow fibers

membrane consisting of an aliphatic copolymer coated

on a polysulfone support. They were tested for a binary

CH4/CO2 mixture. The parameters such as temperature,

pressure, stage-cut ( flow feedflow permeate )

also known as degree of separation, and feed composition

are studied. The feed gas contains 60% CO2 which needs

to be removed in the permeate stream to increase

the recovery of CH4 on the retentate stream. The pressure

on permeate and retentate side is 405.3 kPa and 101.3 kPa,

whereas, permeability of CO2 and CH4 used is

31.610-10 mol/m2.s.Pa and 8.8110-10 mol/m2.s.Pa, respectively.

The experimental results along with mathematical model

for permeate composition vs stage cut is presented in Fig. 5.

Iran. J. Chem. Chem. Eng. Nasir Q. et al. Vol. 39, No. 5, 2020

244 Research Article

Fig. 4: Specified parameter for hybrid process.

Fig. 5: Comparison of model and experimental data [29]

for CO2/CH4 system.

As shown, a good agreement is obtained between

mathematical model and the experimental results [28].

Sidhoum et al., investigated CO2/N2 and O2/N2 (air)

separation performance using cellulose acetate hollow

fibers with seep gas on the permeate side [29].

The comparison between measured and model prediction

of the two systems without permeate sweeping are plotted

on Fig. 6 (a) and Fig. 6 (b), respectively. For CO2/N2 system

the composition of 40% CO2 and 60% N2 is used.

The pressure on high and low side of the membrane is 404 kPa

and 101.3 kPa, whereas, the permeability of CO2 and N2

used is 63.6 and 3.0510-10 mol/m2.s.Pa, respectively.

In case of O2/N2 system, the pressure on high and low side

of membrane is 708 kPa and 101.3 kPa and the permeability

of O2 and N2 used is 8.67 and 2.8910-10 mol/m2.s.Pa,

respectively. As shown in Fig. 6 (a), the comparison shows

a good agreement between experimental data and model

prediction whereas, Fig. 6 (b), the model over predict

with slightly higher value than the experimental results.

Similarly, data reported by Sada et al. [30] for

the mixture of carbon dioxide and air using asymmetric fiber

cellulose triacetate membranes are also compared with

the model prediction as shown in Fig. 7. The gas mixture used

to get experimental data consists of 50% CO2, 10.50% O2

and 13.10 % N2, respectively. The pressure on high and

low-pressure side of the membrane is 1570 kPa and 101.3 kPa,

whereas, the permeability of CO2, O2 and N2 used is

204.2, 60.2, and 13.110-10 mol/m2.s.Pa, respectively.

Although, the model prediction shown reasonable estimate

with the experimental data, the model predicts slightly

higher than measured data.

Moreover, Pan in 1986, reported experimental data of

hydrogen recovery from ammonia plant purge gas [31].

The composition of the purge gas from ammonia synthesis

consists of 63% H2, 21% N2, 11% CH4, 3% Ar, and 2%

NH3. The experiments were conducted both in countercurrent

and concurrent pattern and shown in Fig. 8(a). As shown,

overall a good agreement was obtained between measured

Stage cut

0.81

0.8

0.79

0.78

0.77

0.76

0.75 C

O2 m

ole

fra

cti

on

in

per

mea

te

0.00 0.10 0.20 0.30 0.40 0.50

Model prediction

Experimental data

Iran. J. Chem. Chem. Eng. A Hybrid Membrane-Absorption Process for Carbon Dioxide Capture: ... Vol. 39, No. 5, 2020

Research Article 245

Fig. 6: Comparison of model prediction and experimental data.

Fig. 7: Comparison of model and experimental data [31] for

CO2/Air system.

data and model prediction. For the countercurrent

pattern, the results are in good agreement, while for

the co-current pattern, small discrepancies are shown

for higher stage cut.

Similarly, Pan et al., also reported experimental data

of separation of CO2/H2S from sour gas mixture. The feed

composition of CO2 is 48.5 % that is removed

in the permeate stream, to increase the recovery of CH4

on the retentate stream temperature and pressure conditions

of 10°C and the 3,528 kPa on feed stream and 92.8 kPa

on permeate stream are used during the experimental

findings, respectively [31]. As seen in Fig. 8(b), the results

between the model prediction and the experiment result is

good agreement with each other. In this study, key

emphasis is on the recovery and rejection of CH4 and CO2,

therefore, further investigate was carried out on parameters

such as feed pressure, membrane area and recovery rate

on permeate and retentate side.

Effect of operating charactistics on membrane

Feed pressure & recovery of CH4/CO2 on retentate and

permeate side

The effect of feed pressure on the recovery of methane

and CO2 on the retentate and permeate side along with

the area of the membrane are depicted in the Fig. 9 (a&b).

As shown on Fig. 9a, as the pressure increase, the recovery

of CO2 on the permeate side also increases, since CO2 is more

permeable in the membrane. It is evident that higher feed-

side pressure led to a greater pressure drop on both sides

of the membrane creating a driving force for membrane

separation. In contrast, as the pressure increases,

the methane recovery in the retentate side is increases (Fig. 9b).

As shown in the picture (zoomed) the effect of pressure

on methane recovery is prominent between 0 – 4 bar whereas,

high pressure has negligible effect on recovery of methane.

Moreover, as shown in Fig. 9b, the membrane area

decreases as the pressure increases [32].

CO2 in feed & membrane area & CH4 recovery

on retentate side

The effect of feed composition on methane recovery

for the stage cut of 0.25 is illustrated in Fig. 10. As evident

in Fig. 9(a&b), CH4 recovery on retentate and CO2 recovery on

permeate side are prominent between at pressure between

(0 - 0.4) bar therefore, in the composition study feed and permeate

side pressure is maintained at 1.20e-3 and 0.4 bar respectively.

It can be observed that increase in CO2 in the feed gas reduced

the methane recovery in the permeate side.

Also, the total membrane area for effective separation

of CH4 in the retentate side decreases with increase in CO2

concentration (20 – 70%) in the feed gas [5].

Stage cut

1.0

0.8

0.6

0.4

0.2

0.0 C

O2 m

ole

fra

cti

on

in

per

mea

te

0.00 0.10 0.20 .30 0.40 0.50 0.60

Stage cut

0.45

0.40

0.35

0.30

0.25

0.20

0.15

0.10

0.05

0.00

O2 m

ole

fra

cti

on

in

perm

ea

te

0.00 0.10 0.20 0.30 0.40 0.50 0.60

Stage cut

1

0.8

0.6

0.4

0.2

0 C

O2 m

ole

fra

cti

on

in

per

mea

te

0.00 0.20 0.40 0.60 0.80

Model prediction

Experimental data Model prediction

Experimental data

Model prediction

Experimental data

Iran. J. Chem. Chem. Eng. Nasir Q. et al. Vol. 39, No. 5, 2020

246 Research Article

Fig. 8: Comparison of model and measured data of (a) H2, (b) CO2 recovery from purge gas from ammonia plant.

Fig. 9: Effect of pressure on (a) recovery of CO2 and on membrane area, (b) recovery of CH4 in the retentate side.

Fig. 10: Effect of CO2 mole fraction in feed on CH4 retentate

recovery and membrane area.

Analysis of Hybrid membrane and Amine absorption

process

A standard process flow sheet was simulated using

Aspen HYSYS V10, as shown in Fig. 4. The specification

for the standard base simulation along with amine base

solvent used is also shown. The amine package consisting

of the non-ideal Acid Gas-Chemical Solvent equation of

state was used. The package incorporated into latest

version of Aspen HYSYS V10, selectively considers acid

gases, mainly CO2 and H2S, and amines such as DEA,

DGA, DIPA, MDEA, MEA, PZ, TEA, respectively.

Operating conditions and amine strength are considered

for all hybrid processes using different amine solutions.

Equation of State (EoS) validation with experimental

data

The equation of state used in this study is validated

with experimental solubility data from literature using amine

as MDEA, MEA and DEA. The sources for the experimental

data are shown in the Table 2 – Table 4, whereas,

the comparison of experimental and predicted value from

EoS is illustrated in the Fig. 11 – Fig. 13, respectively.

Stage cut

1.00

0.95

0.90

0.85

0.80

0.75

0.70

0.65

0.60 Perm

eate

co

nc,

H2 m

ole

fra

c

0.30 0.35 0.40 0.45 0.50 0.55 0.60 0.65

Stage cut

1.00

0.95

0.90

0.85

0.80

0.75

0.70

0.65

0.60 Perm

eate

co

ncen

tra

tio

n,

CO

2

0.30 0.35 0.40 0.45 0.50 0.55 0.60 0.65

Feed pressure (bar)

78

76

74

72

70

68

66

CO

2 r

ecov

ery

in

perm

eate

0 1 2 3 4 5 6 7 8 9 10

Feed pressure (bar)

95

90

85

80

75

70

65

60

CH

4 r

ecov

ery

in

rete

nta

te

0 20 40 60 80 100

8000

6000

4000

2000

0

Mem

bra

ne a

rea

(m2)

Feed CO2 mole fraction

100

98

96

94

92

90

88

Rete

nta

te C

H4 r

eco

very

(%

)

0 0.2 0.4 0.6 0.8

10000

8000

6000

4000

2000

0

Mem

bra

ne a

rea

(m2)

Model prediction

Experimental data

Model prediction Experimental result (countercurrent) Experimental result (concurrent)

CO2 recovery in permeate

Retentate CH4 recovery (%)

Membrane area

Methane recovery Membrane area

Iran. J. Chem. Chem. Eng. A Hybrid Membrane-Absorption Process for Carbon Dioxide Capture: ... Vol. 39, No. 5, 2020

Research Article 247

Table 2: Loadings (α) values of CO2 in MEA at different concentration (C), temperature (T) and pressure (P).

Researcher T/oC C (mole/litre) Alpha P/kPa NDP Ref

Jones et al. 40, 60, 80, 100, 120, 140 15.25 0.017 - 0.728 0.00266 - 930.990 54 [34]

Lee & Mather 40, 100 15.25, 30.5 0.139 - 1.19 1.15142 - 6616 45 [35]

Lee & Mather 40, 100 30.5 0.067 - 1.00 0.068947 - 6894.7 22 [36]

Lee & Mather 25, 40, 60, 80, 100, 120 6.1, 15.25, 22.875, 30.5 0.065 - 2.152 0.1 - 10000 256 [36]

Lawson & Garst 40, 60, 80, 93.333, 100, 120, 134.44, 140 15.25, 30.5 0.11 - 0.998 1.33 - 2784.44 24 [37]

Lee & Mather 40, 100 15.25 0.074 - 1.166 0.1 - 7000 22 [36]

Nasir & Mather 100 30.5 0.004 - 0.199 0.00214 - 2.96 38 [38]

Isaacs et al. 80, 100 15.25 0.035 - 0.315 0.0066 - 1.75 19 [39]

Shen & Li 40 15.25 0.561 - 1.049 15.7 - 2550 13 [40]

Dawodu & Meisen 100 25.62 0.541 - 0.723 455 - 3863 5 [41]

Jou & Mather 0, 25, 40, 60, 80, 100, 120, 150 30 0.536 - 1.331 82 - 19954 60 [42]

Mamun & Nilsen 120 30 0.155 - 0.4182 7.354 - 191.9 19 [43]

Aronu et al. 40, 60, 80, 100 15, 30, 45, 60 0.0017 - 0.565 0.0007 - 478.99 147 [44]

Tonga et al. 40, 60, 80, 100, 120 30 0.0446 - 0.965 3.95 - 983.5 60 [45]

Table 3: Loadings (α) values of CO2 in MDEA at different concentration (C), temperature (T) and pressure (P).

Researcher T/oC C (mole/litre) Alpha P/kPa NDP Ref

Jou et al. 25, 40, 70, 100, 120 23.34, 48.9 0.00037 - 1.833 0.00161 - 6380 120 [46]

Chakma & Meisen 100, 140, 160, 180, 200 19.8, 48.9 0.021 - 1.304 103 - 4930 75 [47]

Mac Gregor & Mather 40 23.34 0.124 - 1.203 1.17 - 3770 5 [48]

Shen and Li 40, 60, 80, 100 30 0.189 - 1.108 1.1 - 1979 45 [40]

Jou et al. 40, 100 35 0.002 - 0.271 0.004 - 262 37 [49]

Dawodu & Meisen 100, 120 48.9 0.123 - 0.497 162 - 3832 12 [41]

Kuranov et al. 40, 60, 100, 120, 140 18.8, 19.2, 32.1 0.184 - 1.2514 73.5 - 5036.7 78 [48]

Mathonat et al. 40, 70, 100 30 0.87 - 1.26 2000 - 10000 9 [50]

Silkenbaumer et al. 40 30 0.24 - 1.206 12.01 - 4080 10 [51]

Lemoine et al. 24.55 23.63 0.0171 - 0.2625 0.02 - 1.636 13 [52]

Park & Sandall 50, 75, 100 50 0.015 - 0.4884 0.78 - 140.4 30 [53]

Kamps et al. 40 , 70, 100 32, 48.8 0.126 - 1.243 176.5 - 7565 28 [54]

Boumedine et al. 25, 40, 65 25.73, 46.88 0.008 - 1.288 2.96 - 4560 85 [55]

Mamun et al. 55, 75, 85 50 0.1658 - 0.6898 65.75 - 813.4 37 [43]

Ermatchkov et al. 40, 70, 100 18.5 - 48.9 0.003194 -

0.7233 0.12 - 63.9 101 [56]

Derks et al. 40 23.34 0.122 - 0.81 1.25 - 93.6 10 [57]

Najibi & Maleki 25, 40, 60, 70, 80, 100, 120 23.34, 48.9 0.083 - 0.83 30.8 - 82.91 14 [58]

Iran. J. Chem. Chem. Eng. Nasir Q. et al. Vol. 39, No. 5, 2020

248 Research Article

Table 4: Loadings (α) values of CO2 in DEA at different concentration (C), temperature (T) and pressure (P).

Researcher T/oC C (mole/litre) Alpha P/kPa NDP Ref

Lee et al. 0, 25, 50, 75, 100, 120, 140 5.25, 20.6, 35.4, 49.7, 63.7,

77.6 0.015 - 2.695 0.69 - 6894.743 322 [59]

Lee et al. 25, 50, 75, 100, 120 5.25, 20.6, 35.4, 49.7 0.022 - 2.695 0.69 - 6894.743 163 [60]

Lee et al. 50 20.6 0.04 - 1.281 0.07 - 6894.743 11 [35]

Lawson & Garst 37.78, 65.56, 79.44, 93.33. 107.22,

121.11 25 0.32 - 1.167 1.99 - 4372 37 [37]

Kennard & Meisen 100, 110, 120, 130, 140, 150, 160,

170, 180, 190, 200, 205 10, 20, 30 0.193 - 1.427 91 - 3746.7 133 [61]

Lal et al. 40, 100 20.6 0.005 - 0.367 0.002 - 3.34 44 [62]

Dawodu & Meisen 100 42.1 0.299 - 0.725 93 - 3742 6 [41]

Rogers et al. 50 20.2 0.006 - 0.233 0.0003 - 0.55 14 [63]

Boumedine et al. 25, 75 41.78 0 - 1.088 2.46 - 4662.7 26 [55]

Seo & Hong 40, 60, 80 30 0.404 - 0.727 4.85 - 357.3 16 [64]

Young Eun Kim et al. 40, 60, 80 30 0.279 - 0.502 115 3 [65]

Fig. 11: Experimental vs predicted loading data () of CO2 in

MEA.

Analysis of Hybrid membrane and Amine absorption

The quantitative comparison between experimental

data points and simulation results are made using Absolute

Deviation percentage (AD %) as

%100. AD%

exp

exp

calc

(1)

The Mean Absolute Percentage Error (MAPE) is

calculated using the following equation

%100. 1

MAPE

exp

exp

calc

n

(2)

Where ‘’ is loading of acid gas, subscripts ‘cal’ and

‘exp’ represents calculated and experimental values and

‘n’ represent number of data points.

The literature solubility data for MEA, from various

source as shown in Table 2 is compared with the EoS

model prediction and illustrated on Fig. 11. Overall

a reasonable agreement is obtained between EoS model

prediction and the experimental, whereas, a divergence

in result is attained at some data points at low pressure

conditions [32, 33]. It is evident from the literature that

most of the model performs poorly at low loading

conditions. The mean error between experimental and

calculated CO2 loading is less than 20%.

Similarly, literature solubility data of CO2 in MDEA

are collected from different source as shown in Table 3.

The literature data are used for the comparison study

with the simulated result. As shown in Fig. 12, both

experimental and the model (EoS) prediction shown

reasonable estimation with the experimental data.

The mean error between experimental and calculated CO2

loading is less than 20%. As illustrated in Fig. 9,

in combination with Fig. 12, at low pressure (0-1) bar,

the deviation between experimental and simulated

are large and it improves at higher pressure.

Moreover, the comparison study is further extended

to the solubility of CO2 in DEA at various conditions.

The literature data is collected from different sources as shown

in Table 4, is compared with the simulated result from

the model (EoS) used in this work. Fig. 13, shows

Experimental

2

1.5 1

0.5

Pred

icte

d

0.5 1 1.5 2

Iran. J. Chem. Chem. Eng. A Hybrid Membrane-Absorption Process for Carbon Dioxide Capture: ... Vol. 39, No. 5, 2020

Research Article 249

Fig. 12: Experimental vs predicted loading data () of CO2

in MDEA.

Fig. 13: Experimental vs predicted loading data () of CO2

in DEA.

the comparison between prediction and experimental data

points. Overall, the prediction provides a reasonable

estimate with the literature data. Similar to previous

reported results, the mean error between experimental and

calculated CO2 loading is less than 19%.

Effect of lean loading of CO2 on the reboiler duty

Number of stages in absorber and stripper of amine

absorption process are arbitrarily chosen to be 10 and 20,

respectively. The number of stages required for both

the absorber and regenerator columns were optimized

in simulation to minimize the reboiler duty. The effect

on the reboiler duty was studied by varying the lean loading of CO2

from 0.05 – 0.4, for different amine solution such as MDEA,

MEA, DEA, TEA, DGA, DIPA and MDEA+ MEA.

Different CO2 concentration in feed to amine unit (5, 15

and 20%) are used in the study. However, due to similar overall

trends only 20 mol % of CO2 in the feed is shown here.

Fig. 14, shows the effect of lean loading of various

amines on the reboiler duty for a targeted CO2 recovery and

purity when a CO2 concentration in the feed gas to amine

unit is 20 mol%. As compared in Fig. 14, for various

amines studied, the required heat duty decrease as the lean

loading increases. In comparison with other amines, MEA

consumed higher reboiler duty, whereas, for DEA is the

lowest. Moreover, the slope of reboiler heat duty curve for

MEA, are steeper between lean loadings of 0.05 to 0.25,

whereas, for DEA almost invariant change in slope

in curve is observed.

As shown in Fig. 14, for both MEA and DEA, the slope

of the curve decreases with increase in lean loading and

the optimized reboiler heat duty is found to be proportional

to the lean loading value of 0.30, which is approximately

1.25e5 kW. Also at lean loading of 0.05 (mol of CO2/mol

of MEA or DEA), a large amount of heat is required

(approx. 1.9e5kW) at the reboiler to separate the desired

CO2. Similarly, at low solvent circulation rate, heat energy

consumed by the reboiler to separate the CO2 is very high.

Therefore, at low lean CO2 loading, a significant amount

of additional energy is required during regeneration

process. As the lean loading is increases the reboiler duty

start to decrease until it reaches to a plateau above 0.30.

Further, increase in lean loading of CO2, the slope of

the curve become linear.

Consequently, the amine solution with a higher CO2

loading can be regenerated more easily with low reboiler

duty as compared to lower CO2 loading with high reboiler

duty. Moreover, the CO2 loading of lean solution against

reboiler duty need to be adjusted so that the energy

consumption at the regeneration unit can be reduced, while

keeping the target capture performance. This also helps

in overall reduction in cost of the capture process.

Furthermore, it is also worth to discuss the comparison

between the different CO2 lean-loading of different amines

on reboiler heat duty. Due to lower heat of reaction

and latent heat of vaporization, DEA, offers better energy

savings than MEA [66]. Conversely, lean CO2 loading

with other solvents such as MDEA, TEA, DGA, DIPA

and combination of MDEA + DEA, shows even better result

of energy reduction. The get clear illustration and comparison

Fig. 10 is zoomed. As shown that DGA, offers the lowest

overall reduction in reboiler heat duty for regeneration.

Experimental

2

1.5

1

0.5

0

Pred

icte

d

0 0.5 1 1.5 2

Experimental

2.5 2

1.5

1

0.5

0

Pred

icte

d

0 0.5 1 1.5 2 2.5

Iran. J. Chem. Chem. Eng. Nasir Q. et al. Vol. 39, No. 5, 2020

250 Research Article

Fig. 14: Reboiler duty for the targeted CO2 recovery and purity when lean loading varies from 0.05 to 0.40 (mol CO2/ mol amines)

for high CO2 in feed.

Fig. 15: Reboiler heat duties at different CO2 concentration with lean loading (a) MEA and (b) DEA.

Moreover, the reboiler duty required to treat different gas

mixture to design specification was investigated for other

feed gas to amine unit with concentration of CO2 varies to

5, 15 and 25%, respectively.

After testing all solvents and considering similar effects

on the reboiler duty at the studied concentrations plotted

against lean loading, only MEA and DEA are selected for

illustration as shown on Fig. 15 (a) and Fig. 15 (b),

respectively. As shown, the reboiler duty decreases and

reaches to a plateau for a lean loading of 0.25 afterwards.

It is also obvious that the MEA is more advantageous when

the CO2 content in the feed gas mixture is lower. A similar

behavior is seen in case of DEA.

In literature there is no such evidence that hybrid amine

membrane setup offer any advantages for the post-

combustion CO2 removal [21]. Moreover, both membrane

and amine were studied as series and in parallel

arrangement and it was concluded that the hybrid setup

consist of membrane and MEA might not be a good choice

for post-combustion CO2 capture.

The standalone in comparison with hybrid process

utilizes the lowest energy [21, 66]. It is coherent from Fig. 15,

that as the CO2 concentration increases, the reboiler duty

also increases. In the literature, membranes unit are used

as multistage membrane setup with or without permeate or

retentate recycle. However, to further gain insights

into how the hybrid system performs, in particular using

different amines used in separation process. It is preferable

to arrange the configuration in a most straight forward

consist of single stage membrane and Amine unit setup,

as shown in Fig. 4.

Effect of CO2 concentration in the feed on the total

energy, with or without membrane unit

The total energy consumed in cooler, pump,

regenerator reboiler and regenerator condenser in

Lean loading, mol of CO2 / mol of MEA

4.2E+05

3.6E+05

3.0E+05

2.4E+05

1.8E+05

1.2E+05

6.0E+04

0.0E+00

Reb

oil

er d

uty

, k

W

0.00 0.10 0.20 0.30 0.40 0.50

Lean loading, mol of CO2 / mol of DEA

0.00 0.10 0.20 0.30 0.40

2.0E+04

1.5E+04

1.0E+04

5.0E+03

0.0E+00

Reb

oil

er d

uty

, k

W

2.0E+05

1.5E+05

1.0E+05

5.0E+04

0.0E+00

Reb

oil

er d

uty

, k

W

Lean loading, mol of CO2 / mol of MEA

0.00 0.10 0.20 0.30 0.40 0.50

Lean loading, mol of CO2 / mol of MEA

0.00 0.10 0.20 0.30 0.40 0.50

5.0E+04

4.0E+04

3.0E+04

2.0E+04

1.0E+4

Reb

oil

er d

uty

, k

W

0.0E+00

Iran. J. Chem. Chem. Eng. A Hybrid Membrane-Absorption Process for Carbon Dioxide Capture: ... Vol. 39, No. 5, 2020

Research Article 251

Fig. 16: Total energy consumed with/without membrane vs CO2 composition in feed.

alkanolamine unit of hybrid unit (amine & membrane) are

studied at various feed gas concentration. Different amines

such as MDEA, MEA, DEA and DEA+MDEA are

selected in this study along with CO2 whose concentration

varies from 0.1 – 0.5 mole %, while keeping the H2S

concentration to 0.1 mole %. The rest of the condition used

in this case study is illustrated in Table 5. As shown in Fig. 16,

overall the total energy consumed using standalone amine

process or hybrid setup consist of amine and membrane

increases with increase CO2 composition in the feed.

However, reduction in total energy is observed when

hybrid setup is used as compared to amine unit

as individual process.

Moreover, the comparison of total energy consumed

in hybrid system, for various amine solution, and by various

CO2 concentration in the feed is also studied and illustrated

in Fig. 17. The results shows, with MDEA used in amine

absorption process, the total energy consumed is

the highest and MEA is the lowest.

Fig. 17: Total energy consumed with different amines in hybrid

setup with increase in CO2 composition in feed.

Also, from Fig. 17, among membrane and amine unit,

amine adsorption process consumes more energy unlike

membrane process where no addition energy is required

to boast the permeation and rejection.

2.5E+04

2.0E+04

1.5E+04

1.0E+04

5.0E+03

0.0E+00

To

tal

en

ergy

(k

W)

Mole fraction of CO2 in feed (%)

0.00 0.10 0.20 0.30 0.40 0.50 0.60

2.5E+04

2.0E+04

1.5E+04

1.0E+04

5.0E+03

0.0E+00

To

tal

en

ergy

(k

W)

Mole fraction of CO2 in feed (%)

0 0.1 0.2 0.3 0.4 0.5 0.6

2.5E+04

2.0E+04

1.5E+04

1.0E+04

5.0E+03

0.0E+00

To

tal

en

ergy

(k

W)

Mole fraction of CO2 in feed (%)

0.00 0.10 0.20 0.30 0.40 0.50 0.60

2.5E+04

2.0E+04

1.5E+04

1.0E+04

5.0E+03

0.0E+00

To

tal

en

ergy

(k

W)

Mole fraction of CO2 in feed (%)

0 0.1 0.2 0.3 0.4 0.5 0.6

1.8E+04

1.5E+04

1.2E+04

9.0E+03

6.0E+00

To

tal

en

ergy

(k

W)

Mole fraction of CO2 in feed (%)

0.00 0.10 0.20 0.30 0.40 0.50 0.60

Iran. J. Chem. Chem. Eng. Nasir Q. et al. Vol. 39, No. 5, 2020

252 Research Article

CONCLUSIONS

The study focus on studying various amines used

in absorption process and its effect on energy penalty,

considering standalone amine process or hybrid setup

consist of single stage membrane and amine process.

The membrane with multi-stage configuration are always

advantageous, however, single permeator setup with

complete mixing model are chosen for simple and quick

computation response. As different amines are tested

in amines absorption process, the overall energy requirement

in hybrid process was significantly reduced, whereas,

the MEA capture offers more advantageous with energy

penalty to its lowest as compared to other amines used.

Furthermore, the new EoS in Aspen HYSYS, produced

a reasonable estimate of CO2 solubility in amines which

confirms its suitability in acid gas recovery unit.

Acknowledgment

This study was done with the financial support from

the University of Nizwa, Oman.

Received : Mar. 6, 2019 ; Accepted :Jul. 1, 2019

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